Mean-field constraints restore sparsity in Potts machines by replacing dense pairwise constraint couplings with dynamically updated single-node biases, achieving comparable partitioning quality with reduced density and accelerated FPGA performance.
Application of statistical me- chanics to np-complete problems in combinatorial opti- misation.Journal of Physics A: Mathematical and Gen- eral, 19(9):1605, jun 1986
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Restoring Sparsity in Potts Machines via Mean-Field Constraints
Mean-field constraints restore sparsity in Potts machines by replacing dense pairwise constraint couplings with dynamically updated single-node biases, achieving comparable partitioning quality with reduced density and accelerated FPGA performance.